Consiglio Nazionale delle Ricerche

Tipo di prodottoArticolo in rivista
TitoloArtifical intelligence technology in cancer imaging: Clinical challenges for detection of lung and breast cancer
Anno di pubblicazione2019
  • Elettronico
  • Cartaceo
Autore/iCoccia Mario
Affiliazioni autoriCNR, National research Council of Italy & Yale University School of Medicine, USA
Autori CNR e affiliazioni
  • inglese
AbstractIn the domain of Artificial Intelligence, deep learning is part of a broader family of machine learning methods based on deep neural networks, deep belief networks, recurrent neural networks and convolutional neural networks that have been applied to fields including computer vision, medical image analysis, histopathological diagnosis, with results comparable to and in some cases superior to human experts. This study shows that these methods applied to medical imaging can assist pathologists in the detection of cancer subtype, gene mutations and/or metastases for applying appropriate therapies. Results show that trajectories of AI technology applied in cancer imaging seems to be driven by high rates of mortality of some types of cancer in order to improve detection and characterization of cancer to apply efficiently anticancer therapies. This new technology can generate a technological paradigm shift for diagnostic assessment of any cancer type. However, application of these methods to medical imaging requires further assessment and validation to support the efficiency of the workflow of pathologists in clinical practice and improve overall healthcare sector.
Lingua abstractinglese
Altro abstract-
Lingua altro abstract-
Pagine da82
Pagine a98
Pagine totali16
RivistaJournal of social and administrative sciences
Attiva dal 2014
Editore: KSP Journals - Istanbul
Paese di pubblicazione: Turchia
Lingua: inglese
ISSN: 2149-0406
Titolo chiave: Journal of social and administrative sciences
Titolo proprio: Journal of social and administrative sciences
Titolo abbreviato: J. soc. adm. sci.
Numero volume della rivista6
Fascicolo della rivista2
Verificato da refereeSì: Internazionale
Stato della pubblicazionePublished version
Indicizzazione (in banche dati controllate)
  • Scopus (Codice:0)
  • Google Scholar (Codice:0)
  • RePEc: Research Papers in Economic (Codice:0)
  • EconLit (Codice:0)
  • ResearchGate (Codice:0)
  • Academia Edu (Codice:0)
Parole chiaveArtificial intelligence, Diagnostic assessment, Histopathology images, Deep learning algorithms, Cancer, Clinical challenges, Technological Change, technological evolution
Link (URL, URI)
Titolo parallelo-
Scadenza embargo-
Data di accettazione-
Note/Altre informazioniCoccia M. 2019. Artifical intelligence technology in cancer imaging: Clinical challenges for detection of lung and breast cancer. Journal of Social and Administrative Sciences, vol. 6, n. 2, pp. 82-98,, ISSN: 2149-0406,
Strutture CNR
  • IRCRES — Istituto di Ricerca sulla Crescita Economica Sostenibile
Moduli/Attività/Sottoprogetti CNR-
Progetti Europei-